The present invention relates to apparatus and methods for classifying a moving vehicle, and has particular relation to such methods and apparatus which are simple, cheap, and compact, and have light weight and low power.
A moving land vehicle radiates seismic waves. A moving sea vehicle produces a bow wave and a wake. A rocket plume emits infrared radiation. All moving vehicles make noise. Metallic moving vehicles have a radar return signal which is different from that of the same vehicles when stationary. They also produce minute changes in the magnetic and gravitational field surrounding the vehicle. These and other emanations from a moving vehicle form, in total, the signature of the vehicle. The signature may be detected by IR detectors, seismometers, gravitometers, magnetometers, sonar and radar receivers, and other sensors.
Capturing the signature, while necessary, is only half the battle. The other half is interpreting the raw output of the sensors. A sudden increase in seismic energy may not indicate a passing vehicle. It may only be an animal, or the wind blowing an empty barrel down the road. It Is important to be able to filter out background signals, and to determine that It really was a vehicle which passed. It is likewise important to be able to tell the class of the vehicle: its kind, direction, speed, probable cargo, etc. In short, the vehicle must be classified both as a vehicle and as a particular class of vehicle, and this classification must be done in the presence of a confusing background.
The prior art has attempted to do so by first determining various characteristics of the purported vehicle: how far it depressed the ground, how far Its front wheels were from its rear wheels, etc. If the characteristics were absurd (for example, a road vehicle with a ground depression suitable for a tractor-trailer, but a wheelbase suitable for a bicycle), the conclusion was reached that something else was present (an elephant, perhaps). If both the ground depression and the wheelbase were suitable for a tractor-trailer, then we assume that was what was indicated.
Determining vehicle characteristics is a complicated process. On the other hand, it has been equally frustrating to try to match raw sensor output collected under field conditions with raw sensor output stored in a library collected from known vehicles under known conditions.